{"id":"W4405056104","doi":"10.1371/journal.pone.0314746","title":"Coordination strategies to improve COVID-19 PCR laboratory testing scale up in Nepal: An analysis","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"UNICEF; World Health Organization","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Sample (material); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Test strategy; Diagnostic test; 2019-20 coronavirus outbreak; Scale (ratio); Business; Risk analysis (engineering); Computer science; Outbreak; Medicine; Virology; Veterinary medicine; Geography; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003882283,0.000405796,0.0003165473,0.0008104252,0.0006789028,0.002487472,0.001166211,0.0006540973,0.005597888],"category_scores_gemma":[0.01242196,0.0002941304,0.0005280245,0.0008138073,0.0005737292,0.001794737,0.002395724,0.0007599631,0.0002538423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005042387,"about_ca_system_score_gemma":0.006390322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03602221,"about_ca_topic_score_gemma":0.0364368,"domain_scores_codex":[0.9972139,0.001410879,0.00007549651,0.000217193,0.0002436622,0.0008388949],"domain_scores_gemma":[0.9944761,0.002772956,0.001024406,0.0002037363,0.00089011,0.0006327513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007547468,0.0008802172,0.3197956,0.0008942946,0.0007849874,0.002055713,0.003484505,0.4395256,0.003182974,0.1015251,0.01306758,0.1140485],"study_design_scores_gemma":[0.0005073243,0.002087947,0.2809941,0.0005687564,0.0008017661,0.0004545696,0.01963028,0.625463,0.002706738,0.03157112,0.03508659,0.0001277129],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9433199,0.0008417304,0.01499936,0.007558038,0.00004092851,0.0005176708,0.0009946371,0.0001048058,0.03162285],"genre_scores_gemma":[0.9968829,0.0002050152,0.001686366,0.0001767977,0.000006700925,0.00007644743,0.0001093186,0.000007386006,0.0008492442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03602221,"threshold_uncertainty_score":0.07162511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1062549221187742,"score_gpt":0.3340902269286204,"score_spread":0.2278353048098462,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}